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AuthorAl-Abbasi, Abubakr O.
AuthorHamila, Ridha
AuthorBajwa, Waheed U.
AuthorAl-Dhahir, Naofal
Available date2023-04-04T09:09:06Z
Publication Date2016
Publication NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
ResourceScopus
URIhttp://dx.doi.org/10.1109/SPAWC.2016.7536774
URIhttp://hdl.handle.net/10576/41608
AbstractIn this paper, we propose a general framework that transforms the problems of designing sparse finite-impulse response channel-shortening equalizers and target impulse response filters for multiple antenna systems into the problems of sparsest-approximation of a vector in different dictionaries. Additionally, we compare several choices of the sparsifying dictionaries in terms of the worst-case coherence metric, which determines their sparsifying effectiveness. Furthermore, a reduced complexity design approach is proposed, which is realized by exploiting the asymptotic equivalence of Toeplitz and circulant matrices. Finally, the significance of our proposed approach is demonstrated through numerical experiments. 2016 IEEE.
Languageen
PublisherIEEE
SubjectEqualizers
Impulse response
Wireless telecommunication systems
Asymptotic equivalence
Circulant matrix
Finite impulse response channels
Multiple antenna systems
Numerical experiments
Reduced complexity
Target impulse response
Worst-case coherences
Signal processing
TitleSparsifying dictionary analysis for FIR MIMO channel-shortening equalizers
TypeConference Paper
Volume Number2016-August
dc.accessType Abstract Only


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